ArticleThe patient2019
Does Device or Connection Type Affect Health Preferences in Online Surveys?
Article in The patient, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Stated-Preference Survey Design and Testing in Health Applications.The patient · 2025Article
- Did a bot eat your homework? An assessment of the potential impact of bad actors in online administration of preference surveys.PloS one · 2023Article
- Preference Paths and Their Kaizen Tasks for Small Samples.The patient · 2022Article
- Time for Tele-TTO? Lessons Learned From Digital Interviewer-Assisted Time Trade-Off Data Collection.The patient · 2021Article
- Mobilising the Next Generation of Stated-Preference Studies: the Association of Access Device with Choice Behaviour and Data Quality.The patient · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveRecent evidence has shown that online surveys can reliably collect preference data, which markedly decrease the cost of health preference studies and expand their representativeness. As the use of mobile technology continues to grow, we wanted to examine its potential impact on health preferences.
methodsTwo recently completed discrete choice experiments using members of the US general population (n = 15,292) included information on respondent device (cell phone, tablet, Mac, PC) and internet connection (business, cellular, college, government, residential). In this analysis, we tested for differences in respondent characteristics, participation, response quality, and utility values for the 5-level EQ-5D (EQ-5D-5L) by device and connection.
resultsCompared to Mac and PC users, respondents using a cell phone or tablet had longer completion times and were significantly more likely to drop out during the surveys (p < 0.001). Tablet users also demonstrated more logical inconsistencies (p = 0.05). Likewise, respondents using a cellular internet connection exhibit significantly less consistency in their health preferences. However, matched samples for tablets and cell phones produced similar EQ-5D-5L utility values (mean differences < 0.06 on a quality-adjusted life-year [QALY] scale for all potential health states).
conclusionAllowing respondents to complete online surveys using a cell phone or tablet or over a cellular connection substantially increases the diversity of respondents and the likelihood of obtaining a representative sample, as many individuals have cell phones but not a computer. While the results showed systematic variability in participation and response quality by device and connection type, this study did not show any meaningful changes in utility values.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.